Bayesian np control charts with adaptive sample size for finite production runs

Abstract

Abstract The design of a control chart requires the specification of three decision variables, namely the sample size, n, the sampling interval, h, and the action limit under which the process must be stopped for potential repair. In this paper, the Bayesian attribute control chart, namely the np chart for short run production, using a variable sample size is discussed. In a simulated experiment, optimal solutions of the static np chart, the basic Bayesian np chart, and the Bayesian scheme with adaptive sample size are presented. Results of the empirical study show that varying the sample size leads to more cost savings compared with the other two approaches. In order to detect how the input parameters affect decision variables, a regression analysis is conducted. It is obtained that the benefits of using the basic Bayesian np chart and the Bayesian chart with adaptive sample size instead of the static scheme are affected by the length of the production run. Copyright © 2008 John Wiley & Sons, Ltd.

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